Between fact and credence

2014-12-19

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The work of the scientist or the scientifically-minded is to propound propositions about states of affairs backed by epistemic claims. Empirical evidence is the raw data that underpins certain knowledge, in substantiating statements about the actuality and foreseeable potentiality of things.

Within science the “ought” is not of the moral sort — it is methodological. It stands for the alertness the scientist must have in ensuring accurate correspondence between the [regularities of the] facts and the credence underlying any expectation derived therefrom.

On the face of it, the connection between “fact” and “credence” appears as an oxymoron; these notions are typically regarded as diametrical opposites — and in a sense they are. Their relation is nonetheless present and is made manifest in at least a couple of ways: (i) the [in]adequacy of data in describing the constitution of a case, and (ii) the disposition of the one interpreting the results of empirical research.

1. The first concerns the breadth and depth of the data at hand. Suppose the case of a coin toss. There are probabilities attached to the possible outcomes of any single coin toss: heads or tails. The scientist can thus discern the patterns involved in order to document what happens and predict what may happen.

Yet the case under examination is not just one of two possible outcomes as its formal structure suggests, for there are other factors that interoperate in this case, such as the technique in which a coin will be tossed — a variable that may skew the results in one way or another.

To fully capture this case the scientist must therefore ensure their data does not omit such classes of information, else the descriptive and predictive power of their opus would not be robust to credence.

Understandably, the need for this kind of thoroughgoing precision becomes ever more present the greater the complexity of the case.

2. The second scenario is about the vigilance of the researcher — how much belief they are willing to tolerate once they are aware of their data’s relative imperfection.

Consider the work of the economist. The “economy” is a term encapsulating a vast array of interwoven factors that interact in complex ways and to varying degrees to deliver outcomes that can often deviate from the expected ones.

Against this backdrop and given the current state in the development of the science of economics, the imperfection of the data is to be recognised as a [transient] reality.

What remains to be determined is the length to which the economist will go to attach belief in the descriptive capacity and predictive accuracy of their available data and research tools as well as the validity of their corresponding policy prescriptions.

The latter is of particular interest. It is not rare to behold feverish controversies between loud and vociferous economists of opposing schools of thought. These usually occur in the realm of the credences attached to the facts.

All of the above lead to two tentative conclusions about methodology: (a) painstaking care needs to be taken in order to ensure the best possible representation of the case’s constitution, and (b) the scientist “ought to” ensure correspondence between the facts and the arguments based on them.

In a more abstract sense, these can be summarised as the disposition to remain inquisitive and dubitative.